elrm (version 1.2.5)

plot.elrm: Plot Diagnostics for an elrm Object

Description

Produces both a trace plot and histogram of the sampled values of each sufficient statistic of interest. Sampled values within the burn-in period are also plotted.

Usage

# S3 method for elrm
plot(x, p = 1, breaks = "Sturges", ask=FALSE, ...)

Arguments

x

an object of class elrm, resulting from a call to elrm() or a previous call to update().

p

the sampling fraction of points to be plotted. A random sample consisting of p*100% of all the observations in the Markov chain is plotted; default=1.

breaks

a vector giving the number of cells to use for the histogram of each sufficient statistic of interest or a single number giving the number of cells for each histogram or the character string naming an algorithm to compute the number of cells.

ask

the graphics parameter ask: see par for details. If set to TRUE will ask between plots corresponding to each sufficient statistic; default=FALSE.

…

additional arguments to the plot function (currently unused).

Value

No return value. Creates a plot of the sampled sufficent statistics for each parameter of interest.

Details

The default for breaks is "Sturges": see nclass.Sturges. Other names for which algorithms are supplied are "Scott" and "FD".

References

Zamar, D., McNeney, B., & Graham, J. (2007). elrm: Software Implementing Exact-Like Inference for Logistic Regression Models. Journal of Statistical Software, 21(3), 1-18.

Zamar, D., Monte Carlo Markov Chain Exact Inference for Binomial Regression Models. Master's thesis, Statistics and Actuarial Sciences, Simon Fraser University, 2006

Forster, J.J., McDonald, J.W. & Smith, P.W.F. Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models. Statistics and Computing 13, 169-177 (2003).

Geyer, C.J. Practical Markov chain Monte Carlo. Statistical Science, 7:473-511, 1992

See Also

update.elrm, summary.elrm, elrm.

Examples

# NOT RUN {
# Drug dataset example with treatment as the variables of interest
data(drugDat);
drug.elrm = elrm(formula=recovered/n~sex+treatment, interest=~treatment, r=4, 
	iter=2000, burnIn=100, dataset=drugDat);

# Plot the sampled values of the sufficient statistic for the parameter(s) of 
# interest
plot(drug.elrm,p=0.10,ask=TRUE);
# }